Update README.md

README.md

@@ -13,13 +13,12 @@ specifically for expertise on AMD technologies and python coding.
 
 <!-- Provide a longer summary of what this model is. -->
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub.  
-This model card has been automatically generated.
+This is the model card of a 🤗 transformers model that has been  
+pushed on the Hub. This model card has been automatically generated.
 
 - **Developed by:** David Silverstein
-- **Model type:** [More Information Needed]
 - **Language(s) (NLP):** English, Python
-- **License:** [More Information Needed]
+- **License:** Free to use under Llama 3.1 licensing terms without warranty
 - **Finetuned from model meta-llama/Meta-Llama-3.1-8B-Instruct**
 
 ### Model Sources [optional]
@@ -47,7 +46,7 @@ limitations of the model. More information needed for further recommendations.
 
 ## How to Get Started with the Model
 
-Use the code below to get started with the model. 
+Use the code below to get started with the model:
 
 import torch  
 from transformers import AutoTokenizer, AutoModelForCausalLM  
@@ -68,14 +67,8 @@ The training set consisted of 1658 question/answer pairs in Alpaca format.
 
 [More Information Needed]
 
-### Training Procedure
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-[More Information Needed]
-
 #### Training Hyperparameters
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+- **Training regime:** [bf16 non-mixed precision] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
 
 ## Evaluation
 <!-- This section describes the evaluation protocols and provides the results. -->